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The Manager as an Organisation Agent during the Fourth Industrial Revolution

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  • Anna Rogozinska-Pawelczyk

Abstract

Purpose: This paper, which was inspired by challenges faced by organisations transforming towards the Fourth Industrial Revolution (FIR), explores the role of managers as organisation agents in this process. Design/Methodology/Approach: A qualitative method and an interpretative paradigm are used to analyse the outcomes of semi-structured individual in-depth interviews conducted with a purposively assembled sample of 12 managers. Findings: The analysis determined three main thematic threads describing the roles and attributes that the FIR requires of managers. The first thematic thread concerned the impact of the FIR on the functioning of organisations and their employees. The following roles were further identified: talent manager, development initiator, change visionary, and transparent leader. With regard to attributes, strategic thinking, flexibility, and responsiveness to change, creativity and innovation, an ability to cooperate and inspiringly motivate employees, agility in seizing opportunities created by the FIR and an ability to cope with its challenges were indicated as essential. Originality/Value: Based on the study’s findings, a preliminary model of the FIR as the driver of new roles for managers-agents is proposed. The paper makes an important theoretical and practical contribution to the understanding of the essential role of managers-agents during the FIR. It has been prepared in response to the paucity of studies on this subject. The findings of the study are hoped to help managers to better understand their role during the FIR and to adjust to it.

Suggested Citation

  • Anna Rogozinska-Pawelczyk, 2022. "The Manager as an Organisation Agent during the Fourth Industrial Revolution," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 509-529.
    • Handle: RePEc:ers:journl:v:xxv:y:2022:i:2:p:509-529
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    References listed on IDEAS

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    1. Mojtaba Vaismoradi & Hannele Turunen & Terese Bondas, 2013. "Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study," Nursing & Health Sciences, John Wiley & Sons, vol. 15(3), pages 398-405, September.
    2. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    3. Coyle-Shapiro, Jacqueline A-M. & Shore, Lynn M, 2007. "The employee-organization relationship: where do we go from here?," LSE Research Online Documents on Economics 4887, London School of Economics and Political Science, LSE Library.
    4. Min Xu & Jeanne M. David & Suk Hi Kim, 2018. "The Fourth Industrial Revolution: Opportunities and Challenges," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(2), pages 90-95, April.
    5. McIver, Derrick & Lengnick-Hall, Mark L. & Lengnick-Hall, Cynthia A., 2018. "A strategic approach to workforce analytics: Integrating science and agility," Business Horizons, Elsevier, vol. 61(3), pages 397-407.
    6. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    7. Marco Ardolino & Mario Rapaccini & Nicola Saccani & Paolo Gaiardelli & Giovanni Crespi & Carlo Ruggeri, 2018. "The role of digital technologies for the service transformation of industrial companies," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2116-2132, March.
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    More about this item

    Keywords

    Fourth industrial revolution; organizational behaviour; manager as an organisation agent; managers’ roles and attributes.;
    All these keywords.

    JEL classification:

    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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